Abstract
This software includes the Jupyter notebooks, model pretraining and evaluation code for the EXPERT 2.0 Human-AI
Reasoning Engine V0.1. It supports pre-training a Human-AI model for reasoning over multi-layer network representations.
It includes prompt-based evaluation framework in a Jupyter notebook for AI reasoning and Jupyter widgets with AI-based
techniques for evidence generation and uncertainty quantification to support human-AI reasoning.
- Developers:
-
Horawalavithana, Sameera [1] ; Munikoti, Sai [2] ; Wagle, Sridevi [2] ; Acharya, Anurag [2] ; Sharma, Shivam [2]
- Pacific Northwest National Laboratory
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Release Date:
- 2023-10-18
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Licenses:
-
BSD 2-clause "Simplified" License
- Sponsoring Org.:
-
USDOEPrimary Award/Contract Number:AC05-76RL01830
- Code ID:
- 114736
- Site Accession Number:
- Battelle IPID 32848-E
- Research Org.:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Country of Origin:
- United States
Citation Formats
Horawalavithana, Sameera, Munikoti, Sai, Wagle, Sridevi, Acharya, Anurag, and Sharma, Shivam.
pnnl/EXPERT2.
Computer Software.
https://github.com/pnnl/EXPERT2.
USDOE.
18 Oct. 2023.
Web.
doi:10.11578/dc.20231018.1.
Horawalavithana, Sameera, Munikoti, Sai, Wagle, Sridevi, Acharya, Anurag, & Sharma, Shivam.
(2023, October 18).
pnnl/EXPERT2.
[Computer software].
https://github.com/pnnl/EXPERT2.
https://doi.org/10.11578/dc.20231018.1.
Horawalavithana, Sameera, Munikoti, Sai, Wagle, Sridevi, Acharya, Anurag, and Sharma, Shivam.
"pnnl/EXPERT2." Computer software.
October 18, 2023.
https://github.com/pnnl/EXPERT2.
https://doi.org/10.11578/dc.20231018.1.
@misc{
doecode_114736,
title = {pnnl/EXPERT2},
author = {Horawalavithana, Sameera and Munikoti, Sai and Wagle, Sridevi and Acharya, Anurag and Sharma, Shivam},
abstractNote = {This software includes the Jupyter notebooks, model pretraining and evaluation code for the EXPERT 2.0 Human-AI
Reasoning Engine V0.1. It supports pre-training a Human-AI model for reasoning over multi-layer network representations.
It includes prompt-based evaluation framework in a Jupyter notebook for AI reasoning and Jupyter widgets with AI-based
techniques for evidence generation and uncertainty quantification to support human-AI reasoning.},
doi = {10.11578/dc.20231018.1},
url = {https://doi.org/10.11578/dc.20231018.1},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20231018.1}},
year = {2023},
month = {oct}
}